Holistic vehicle control (HVC) methodology may be considered an extension of Holistic Corner Controller (HCC) methodology. Whereas HCC methodology is generally directed to dynamically redistributing tire forces between wheels for vehicle control; HVC methodology is directed to determining the actual individual contributions in vehicle systems using real-time data of each actual physical actuator operating during running of a production vehicle. That is, the physical assistance of each of the produced commercial actuators while in use may have either “opposing” or “collaborative” contributions to the efficacious operations of the vehicle system when viewed with respect to the other actuators performance in the vehicle system when executing a particular task or tasks. These types of individual contributions whether positive or negative of the individual actuators are not realized without using HVC methodologies.
Therefore, it is desirable, given the need for optimal vehicle performance, to make more available the HVC methodologies by generating virtual models of vehicle dynamics for stability and path control, particularly in autonomous vehicles, by defining target goals where realized errors of differences in measured metrics of desired vehicle performance versus actual vehicle dynamics are minimized.
It is desirable to derive sets of optimal empirical solutions for real-time sensing of actual states of the vehicle operations measured or compared against the HVC virtual modeling of these operations to adjust or pre-set the actuator assignments of the vehicle system.
It is desirable to provide improved methods and systems for compensating for vehicle component failures thereby mitigating any resulting undesired performance effects in the vehicle operation. That is, often there are redundant suites of actuators used in vehicle operations which may pose control allocation problems when selecting appropriate sets of actuator to respond to forces or moments detected and further certain actuators may fail or have failed during a vehicle operation.
Therefore, it is desirable to use the HVC virtual modeling and subsequent command transforms to make control selections and decisions of which actuators to use of a redundant actuator set. With respect to failed components, it is desirable to use comparisons of the HVC virtual modeling of vehicle dynamics with actual results to recognize failures of actuators such as electronic limited slip differential (eLSD), powertrain, electronic power steering (EPS) actuator failures, and compensate selectively with different actuators assignments.
It is further desirable to provide methods and systems for determining the control commands using feedback information from the steering, braking, eLSD, and power train vehicle systems.
Current systems may not always provide adequate solutions for a secure, robust and data distribution and interoperable exchange between participants and data providers. Accordingly, it is desirable to provide systems and methods which address these shortcomings. Furthermore, other desirable features and characteristics of the present invention will become apparent from the subsequent detailed description of the invention and the appended claims, taken in conjunction with the accompanying drawings and this background of the invention.